In recent years, deep learning (DL) has been widely studied using various methods across
the globe, especially with respect to training methods and network structures, proving highly …

Neural architecture search (NAS) has become increasingly popular in the deep learning
community recently, mainly because it can provide an opportunity to allow interested users …

Abstract In image Super-Resolution (SR), relying on large datasets for training is a double-
edged sword. While offering rich training material, they also demand substantial …

Deep neural networks have gained great success due to the increasing amounts of data,
and diverse effective neural network designs. However, it also brings a heavy computing …

Dataset distillation has gained significant interest in recent years, yet existing approaches
typically distill from the entire dataset, potentially including non-beneficial samples. We …

The emergence of neural architecture search (NAS) technology has lowered the
professional threshold for optimizing model architectures. However, existing NAS methods …

Hypergraph neural networks (HyperGNNs) show promise in modeling online networks with
high-order correlations. Despite notable progress, training these models on large-scale raw …

Os avanços nos domínios da Inteligência Artificial (IA) e da Aprendizagem Automática (AA)
permitiram obter resultados impressionantes em vários problemas. Estes avanços podem …